Emerging Technology

Introduction to Emerging Technology

Emerging technology refers to new technologies and innovations developing in different fields such as:

Media
Business
Science
Education
Communication
Computing

The term can also refer to the continuous development and improvement of existing technologies.

Some important emerging technologies discussed in this chapter are:

Artificial Intelligence
Cloud Computing
Distributed Computing
Internet of Things
Big Data
Data Mining
Cryptography
Virtual Reality
Augmented Reality

Artificial Intelligence (AI)

Artificial Intelligence (AI) is a branch of computer science concerned with developing machines and computer systems capable of performing tasks that normally require human intelligence.

AI can be described as the simulation of human intelligence by machines.

The chapter identifies John McCarthy with the term Artificial Intelligence and mentions its introduction in 1956.

Characteristics of Artificial Intelligence

Important characteristics of AI include:

Ability to act intelligently.
Ability to perform intelligent actions.
Ability to simulate certain aspects of human intelligence.
Ability to learn and adapt.
Ability to process language and symbols.

Applications of Artificial Intelligence

AI is used in many different fields.

The applications discussed in this chapter include:

Entertainment
Robotics
Gaming
Healthcare
Social Media

1. Entertainment

Artificial intelligence is used by online entertainment and streaming services.

AI and machine-learning systems can study user behaviour and engagement to suggest relevant content.

Examples mentioned in the chapter include:

Netflix
Amazon Prime

Such systems can provide personalized recommendations based on user activity.

2. Robotics

Robotics is one of the important application areas of AI.

Traditional robots may be programmed to perform repetitive tasks.

With AI integration, robotic systems can perform more advanced activities such as:

Monitoring
Analysis
Learning
Decision-making
Improving performance

3. Gaming

Artificial intelligence is widely used in computer and video games.

AI can be used for:

Decision-making
Controlling game characters
Simulating behaviour
Predicting player actions
Creating challenging gameplay

The source gives Alien: Isolation as an example of a game that uses AI behaviour.

4. Healthcare

Artificial intelligence is also used in healthcare.

AI-based systems can assist with:

Disease diagnosis
Medical-data analysis
Identifying abnormal cells
Medical research
Drug discovery

AI can help experts analyze large quantities of medical information.

5. Social Media

Social-media platforms use AI for different purposes.

AI can be used to:

Analyze content
Recommend posts
Display advertisements
Study user engagement
Personalize feeds

Platforms mentioned in the chapter include:

Facebook
Instagram
Twitter
TikTok

Cloud Computing

Cloud computing refers to the delivery of computing services over the Internet.

These services can include:

Storage
Databases
Networking
Software
Computing resources

Cloud computing allows users and organizations to access computing resources without owning and maintaining all the physical infrastructure themselves.

Types of Cloud Computing Services

Cloud computing services are commonly categorized into:

Infrastructure as a Service (IaaS)
Platform as a Service (PaaS)
Software as a Service (SaaS)

1. Infrastructure as a Service (IaaS)

IaaS stands for Infrastructure as a Service.

It provides computing infrastructure through the Internet.

Users may access resources such as:

Virtual Machines
Storage
Networking
Computing Infrastructure

These resources may be provided according to usage requirements.

2. Platform as a Service (PaaS)

PaaS stands for Platform as a Service.

It provides a platform that allows developers to create, run, and manage applications without directly managing all underlying infrastructure.

PaaS may provide:

Operating Systems
Programming-language environments
Runtime environments
Databases
Web Servers
Development Tools

3. Software as a Service (SaaS)

SaaS stands for Software as a Service.

It provides software applications through the Internet.

Users can normally access SaaS applications using a web browser without installing and maintaining the complete software system locally.

Examples listed in the source include:

Google Apps
Microsoft Office 365
Cisco WebEx
Salesforce
Workday

Online email and social-networking services can also operate using similar cloud-based delivery models.

Difference Between IaaS, PaaS and SaaS

Service	Full Form	Main Purpose
IaaS	Infrastructure as a Service	Provides computing infrastructure
PaaS	Platform as a Service	Provides a platform for developing and running applications
SaaS	Software as a Service	Provides ready-to-use software through the Internet

Advantages of Cloud Computing

The major advantages discussed in the chapter are:

Reduced Cost
Storage Service
Reliability
Security

Reduced Cost

Cloud computing can reduce the need for organizations to purchase and maintain large amounts of physical computing infrastructure.

Organizations may use computing resources according to their needs and pay for subscribed or consumed services.

Storage Service

Cloud computing provides scalable storage facilities.

Organizations can increase or reduce their storage requirements according to their needs without depending entirely on local physical storage devices.

Reliability

Cloud-service providers may use multiple systems and data centers to improve reliability and reduce service interruption.

This can help improve system availability.

Security

Cloud platforms may provide different security features for protecting information.

These can include:

Encryption
Identity Management
Access Control
Security Monitoring

Distributed Computing

Distributed computing refers to linking multiple computers together so that they can share data and coordinate processing.

A large task may be divided among several interconnected computers.

Advantages of Distributed Computing

Important advantages include:

Scalability
Improved Performance
Cost-Effectiveness
Reliability

Scalability

Distributed systems can be expanded by adding more computing resources or nodes.

This allows the system to handle increasing workloads.

Improved Performance

Tasks can be distributed among multiple computers.

By performing operations in parallel, processing time may be reduced and overall performance can improve.

Cost-Effectiveness

Distributed systems may use multiple commonly available computing systems instead of relying entirely on a single very powerful computer.

This can make some systems more economical.

Reliability

Since processing can be distributed among several computers, failure of one node does not always require the entire system to stop working.

This can improve fault tolerance.

Internet of Things (IoT)

IoT stands for Internet of Things.

The Internet of Things refers to a network of interconnected devices that communicate and exchange data through the Internet or other connected networks.

IoT devices may collect information from their surroundings and perform actions based on received instructions.

Components of IoT

Important components of an IoT ecosystem include:

Devices
Connectivity
Data Processing and Analytics
User Interface

1. Devices

IoT devices may include:

Sensors
Actuators
Wearable Devices
Vehicles
Appliances
Industrial Machines

These devices may collect information or perform specific actions.

2. Connectivity

IoT devices need communication technologies to exchange information.

The chapter lists technologies such as:

Wi-Fi
Bluetooth
Zigbee
3G
4G
5G
LPWAN
Satellite Communication

3. Data Processing and Analytics

Information collected by IoT devices can be processed and analyzed.

The purpose of analysis is to obtain useful information and support better decisions.

Technologies mentioned in the source include:

Real-Time Processing
Data Mining
Machine Learning
Artificial Intelligence

4. User Interface

A User Interface (UI) allows users to interact with IoT systems.

It can help users:

View information
Monitor devices
Control devices
Check system status

Examples include:

Web Dashboards
Mobile Applications
Command-Line Interfaces
Voice Interfaces

Advantages of IoT

The chapter lists the following advantages:

Efficiency and Automation
Data-Driven Insights
Improved Decision-Making
Enhanced Customer Experience
Cost Savings
Remote Monitoring and Management
Safety and Security
Sustainability

Big Data

Big Data refers to extremely large and complex collections of data that may be difficult to process efficiently using traditional database-management or data-processing methods.

Big Data can be generated from many different sources.

Sources of Big Data

Examples discussed in the chapter include:

Social Media
Stock Exchange
Weather Forecasting
E-Commerce
Bank and Credit-Card Transactions
Scientific Instruments
Mobile Devices

Characteristics of Big Data

The chapter describes the following characteristics:

Volume
Variety
Velocity
Variability

1. Volume

Volume refers to the amount or quantity of data.

Large quantities of information are one of the important characteristics associated with Big Data.

2. Variety

Variety refers to the different types and formats of data.

Data may be:

Structured
Semi-Structured
Unstructured

Data can come from many different sources.

3. Velocity

Velocity refers to the speed at which data is generated, collected, and processed.

Modern systems can generate enormous quantities of data within a short period.

4. Variability

Variability refers to changes and inconsistencies that may occur within data.

Such variation can make data processing and management more difficult.

Data Mining

Data mining is the process of extracting useful information and discovering valuable patterns from large collections of data.

It can help organizations identify patterns and relationships that may be difficult to discover through manual analysis.

Advantages of Data Mining

The major advantages discussed in the chapter are:

Better Marketing
Improved Customer Relationship
Increased Cost Efficiency
Enhanced Employee Productivity

Better Marketing

Data mining can help businesses understand:

Customer Behaviour
Customer Preferences
Purchasing Patterns
Market Trends

This information can help businesses develop more targeted marketing strategies.

Improved Customer Relationship

Organizations can analyze customer:

Feedback
Purchase History
Preferences
Interactions

This can help them understand customer requirements and improve services.

Increased Cost Efficiency

Data mining can help organizations identify inefficient activities and improve business processes.

It may help with:

Demand Forecasting
Inventory Management
Fraud Detection
Process Improvement

Enhanced Employee Productivity

Data mining can provide employees with useful information for better decision-making.

Access to relevant data and analytics can help employees identify problems and opportunities.

Application Areas of Data Mining

The chapter discusses data mining in:

E-Commerce
Insurance
Entertainment
Healthcare
Banking

1. E-Commerce

E-commerce businesses can use data mining to understand:

Customer Behaviour
Product Preferences
Purchase Patterns

It can also be used for recommending products to customers.

2. Insurance

The insurance industry may use data mining for:

Risk Assessment
Fraud Detection
Customer Retention
Claims Analysis

Historical information can be analyzed to identify patterns and evaluate risks.

3. Entertainment

Entertainment platforms can use data mining for:

Content Recommendations
Audience Analysis
User Segmentation
Understanding Viewing Preferences

4. Healthcare

Healthcare organizations can use data mining for:

Medical Data Analysis
Disease Pattern Identification
Patient Management
Risk Analysis
Predictive Analysis

5. Banking

Banks can use data mining for:

Customer Segmentation
Credit Analysis
Fraud Detection
Transaction Analysis
Risk Management

Cryptography

Cryptography is the study and practice of techniques used to protect information and secure communication.

It can be used to help provide:

Confidentiality
Integrity
Authentication
Data Protection

Cryptography involves converting readable data into an unreadable form and later converting it back when required.

Encryption

Encryption is the process of converting readable data, called plaintext, into an unreadable form called ciphertext.

A cryptographic algorithm and key are used during encryption.

Representation

Plaintext → Encryption → Ciphertext

Decryption

Decryption is the reverse process of encryption.

It converts ciphertext back into readable plaintext using the required key.

Representation

Ciphertext → Decryption → Plaintext

Types of Cryptography

The chapter discusses two types:

Symmetric Cryptography
Asymmetric Cryptography

Symmetric Cryptography

In symmetric cryptography, the same secret key is used for both encryption and decryption.

Both the sender and receiver need access to the same key.

Simple Representation

Plaintext → Same Key → Ciphertext → Same Key → Plaintext

Asymmetric Cryptography

Asymmetric cryptography uses two related keys:

Public Key
Private Key

The public key can be shared, while the private key is kept secret.

Difference Between Symmetric and Asymmetric Cryptography

Symmetric Cryptography	Asymmetric Cryptography
Uses one shared key.	Uses a pair of keys.
Same key is used for encryption and decryption.	Uses public and private keys.
Secret key must be shared securely.	Public key can be distributed.
Private shared information must remain secret.	Private key remains secret.

Virtual Reality (VR)

Virtual Reality (VR) refers to a computer-generated simulated environment that can provide users with an immersive experience.

Users commonly experience VR through special hardware such as:

VR Headsets
VR Goggles
Motion Controllers

VR can allow users to interact with and explore computer-generated environments.

Applications of Virtual Reality

The source discusses VR applications in areas such as:

Gaming
Entertainment
Education
Healthcare
Architecture
Engineering
Training
Simulation
Telepresence

Augmented Reality (AR)

Augmented Reality (AR) is a technology that adds digital information or virtual objects to the user’s view of the real-world environment.

The digital elements may include:

Images
Videos
Text
3D Models
Other Virtual Objects

Unlike VR, AR does not completely replace the real environment.

Instead, it combines digital content with the user’s view of the physical world.

Applications of Augmented Reality

The source discusses AR applications in:

Gaming
Education
Retail
Healthcare
Architecture
Manufacturing
Marketing
Navigation

AR can support activities such as:

Product Visualization
Interactive Learning
Remote Assistance
Navigation
Digital Marketing

Difference Between Virtual Reality and Augmented Reality

Virtual Reality (VR)	Augmented Reality (AR)
Creates an immersive virtual environment.	Combines digital content with the real-world environment.
The user interacts mainly with a simulated environment.	The user remains connected with the real environment.
VR headsets are commonly used.	AR can be used through devices such as smartphones, tablets, or specialized displays.
Commonly used in gaming, simulation, and training.	Commonly used for visualization, education, navigation, and demonstrations.
Users may become highly immersed in the virtual environment.	Users can interact with virtual objects while still viewing the real world.

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